rsf2rfz {randomSurvivalForest} | R Documentation |
rsf2rfz
saves a randomSurvivalForest forest object as an .rfz
compressed file that is readable by the RSF Java plugin that is
capable of visualizing the trees in the forest.
rsf2rfz(object, forestName = NULL, ...)
object |
An object of class |
forestName |
The desired prefix name for forest as a string. |
... |
Further arguments passed to or from other methods. |
An .rfz
compressed file is actually a .zip
file
consisting of three files. The first is an ASCII file of type
.txt
containing the $nativeArray
component of the
forest. The second is an ASCII file of type .factor.txt
containing the $nativefactorArray
component of the forest. The
third is an ASCII file of type .xml
containing the PMML
DataDictionary
component.
PMML or the Predictive Model Markup Language is an XML based language which provides a way for applications to define statistical and data mining models and to share models between PMML compliant applications. More information about PMML and the Data Mining Group can be found at http://www.dmg.org.
This function, rsf2rfz
, is used to import the geometry of the
forest to a Java plugin that is capable of visualizing the trees in
the forest.
The geometry of the forest is saved as a file called
forestName.rfz
in the users working directory. This file can
then be read by the randomSurvivalForest Java plugin.
Contact the authors on downloading the Java plugin.
None.
Contact the authors on downloading the Java plugin.
Hemant Ishwaran hemant.ishwaran@gmail.com
Udaya B. Kogalur kogalurshear@gmail.com
http://www.dmg.org
rsf
.
## Not run: # Example 1: Growing a forest, saving it as a \emph{.rfz} file ready # for import into the Java plugin. library("XML") data(veteran, package = "randomSurvivalForest") veteran.out <- rsf(Surv(time, status)~., data = veteran, ntree = 5) veteran.forest <- veteran.out$forest rsf2rfz(veteran.forest, forestName="veteran") ## End(Not run)